Research Methods- data recording, analysis, presentation Flashcards
What is raw data?
Data that has not yet been tampered with/ processed in any way (e.g. scores on a test, tally scores)
What is nominal level data?
Data that can be categorised, but no order/ rank between the categories can be distinguished (e.g. yes/no, red/blue/green)
What is ordinal level data?
Data that can be categorised and ranked in an order, but nothing can be said about intervals between rankings (e.g. placement in a race [1st-10th] with no time record
What is interval level data?
Data that can be categorised, ranked and differences can be identified between data points
This is data measured on a safe numerical scale (e.g. times in seconds to run a 400m lap)
What is primary data?
Results come straight from the source
First-hand
Can be either qualitative or quantitative
What is secondary data?
Data has already been conducted by another researcher
Can be combined with results from similar studies, then re-analysed to create a meta-analysis (e.g. autobiographies, statistics)
What is qualitative data?
Data in a descriptive, detailed form
strength/ weakness of qualitative data?
strength: more detailed= more insight into WHY people behave the way they do
weakness: harder to analyse and compare
What is quantitative data?
Data in a numerical, statistical form
strengths/ weaknesses of quantitative data?
strength: easier to analyse and interpret for comparative purposes (graphs, bar charts)
weakness: much more limited in what it says about WHY
Measures of central tendency- What is the mean?
Average of the data set- add up all response values, divide by total number of responses
(it is only used for interval data)
strengths/ weaknesses of using the mean
strength: most accurate measure of central tendency
weakness: can be distorted by outliers
Measures of central tendency- What is the median?
The value in the middle of the data set- order each value from smallest to largest
(only used for ordinal and interval data)
strengths/ weaknesses of using the mean?
strength: not effected by one off extreme values in data set
weakness: can’t inform us of any extreme values
Measures of central tendency- What is the mode?
Mos popular/common value- can be calculated across all levels of data (only used for nominal data)
strengths/ weaknesses of using the mode?
strength: useful when knowledge of frequency is required
weakness: rarely useful in smaller data sets
Measures of dispersion- What is the range?
The lowest data point is subtracted from the highest data point (only used for ordinal and interval data)
strengths/ weaknesses of using the range?
strength: easy method to identify the difference of the data set
weakness: can be distorted by extreme values